Devstral Small 2 24B Instruct needs ~37.5 GB VRAM. B100 192GB has 192.0 GB. With Q4_K_M quantization, expect ~336 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
336.0 tok/s
TTFT
576 ms
Safe context
256K
Memory
37.5 GB / 192.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 336.0 tok/s | 350 ms | 256K |
| Coding | S | Runs well | 336.0 tok/s | 576 ms | 256K |
| Agentic Coding | S | Runs well | 336.0 tok/s | 838 ms | 256K |
| Reasoning | S | Runs well | 336.0 tok/s | 681 ms | 256K |
| RAG | S | Runs well | 336.0 tok/s | 1048 ms | 256K |
How Devstral Small 2 24B Instruct (24B params) fits at each quantization level on B100 192GB (192.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | A78 |
Q3_K_S | 3 | 11.8 GB | Low | A78 |
NVFP4 | 4 | 13.4 GB | Medium | A78 |
Q4_K_M | 4 | 14.6 GB | Medium | A78 |
Q5_K_M | 5 | 17.3 GB | High | A79 |
Q6_K | 6 | 19.7 GB | High | A79 |
Q8_0 | 8 | 25.7 GB | Very High | A79 |
F16Best for your GPU | 16 | 49.2 GB | Maximum | A82 |
Copy-paste commands to run Devstral Small 2 24B Instruct on your machine.
Run
ollama run devstral-small-2Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 123B | S | 97.4 tok/s | ||
| 30.5B | S | 1016.1 tok/s | ||
| 27B | S | 378 tok/s | ||
| 27B | S | 378 tok/s | ||
| 122B | S | 270.2 tok/s |
Yes, B100 192GB can run Devstral Small 2 24B Instruct with a S grade (Runs well). Expected decode speed: 336.0 tok/s.
Devstral Small 2 24B Instruct (24B parameters) requires approximately 37.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Devstral Small 2 24B Instruct is Q4_K_M, which balances quality and memory efficiency.
On B100 192GB, Devstral Small 2 24B Instruct achieves approximately 336.0 tokens per second decode speed with a time-to-first-token of 576ms using Q4_K_M quantization.
For coding workloads, Devstral Small 2 24B Instruct on B100 192GB receives a S grade with 336.0 tok/s and 256K context.
On B100 192GB, Devstral Small 2 24B Instruct can safely use up to 256K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/devstral-small-2-24b-on-b100-192gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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